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| Section | Objectives |
|---|---|
| Topic 1: Dashboards and Reporting | - Performance dashboards
|
| Topic 2: Diagnostics and Troubleshooting | - Performance bottleneck identification
|
| Topic 3: Monitoring and Instrumentation | - Infrastructure monitoring
|
| Topic 4: Alerting and Business Performance | - Alert configuration
|
| Topic 5: AppDynamics Architecture | - Controller and agents
|
| Topic 6: AppDynamics Fundamentals | - APM concepts and terminology
|
As far as the top standard and relevancy of Prepare for your Cisco AppDynamics Associate Performance Analyst 500-420 valid dumps are concerned, the Cisco Exam Questions are designed and verified by experienced and qualified 500-420 exam experts. They work closely and put all their expertise to ensure the top standard of 500-420 Exam. The updated Cisco AppDynamics Associate Performance Analyst 500-420 exam questions are available in three different but high-in-demand formats.
NEW QUESTION # 112
Which option should a Performance Analyst use in an environment where virtual machines are routinely created and destroyed?
Answer: D
Explanation:
In environments where virtual machines are frequently created and destroyed, using the agent configuration properties-Dappdynamics.agent.reuse.nodeNameand-Dappdynamics.agent.reuse.nodeName.prefixcan be beneficial. These settings allow AppDynamics agents to reuse node names for newly created instances, facilitating consistent monitoring and tracking across dynamic environments. This approach helps maintain clarity in application topology and ensures that performance data remains coherent even as the underlying infrastructure changes.
References:
AppDynamics documentation on Agent Configuration: Discusses advanced agent configuration options, including node name reuse, to accommodate dynamic environments such as those with frequently changing virtual machines.
AppDynamics documentation on Infrastructure Monitoring: Offers insights into best practices for monitoring in dynamic and virtualized environments.
NEW QUESTION # 113
Which two Key Performance Indicators (KPIs) accurately provide insight into server-level resource consumption? (Choose two.)
Answer: D,E
Explanation:
Memory Used% and CPU %Busy are the two KPIs that directly measure server-level resource consumption.
Memory Used% represents the proportion of physical memory currently consumed on the monitored server.
A sustained high value can indicate memory pressure, excessive process allocation, insufficient capacity, or conditions that may lead to paging and degraded application performance.
CPU %Busy measures the percentage of processor capacity actively being used. It is a primary indicator of compute-resource utilization and helps identify CPU saturation, processing bottlenecks, or insufficient server capacity. Persistent high CPU utilization may correlate with increased response time, transaction queuing, and reduced throughput.
The remaining options describe availability, application behavior, or transaction performance rather than direct infrastructure-resource consumption. Calls per Minute measures workload volume, Average Response Time measures transaction latency, Availability indicates whether a system or service is reachable, and Application Restarts records lifecycle events.
Relevant CAAPA Study Guide topics include Server Visibility, Infrastructure Monitoring, Hardware Resource Metrics, CPU Utilization, Memory Utilization, and Correlating Server Health with Application Performance.
NEW QUESTION # 114
What are two differences between creating a Transaction Group using the 'Create Group' action and defining a Transaction Detection rule? (Choose two.)
Answer: A,B
NEW QUESTION # 115
On a snapshot flow map, which three metrics indicate why the snapshot might have been taken? (Choose three.)
Answer: B,C,E
Explanation:
A snapshot flow map presents execution-specific timing information that helps explain why AppDynamics captured that particular transaction instance. The relevant metrics are Thread Blocking Time, Execution Time, and Asynchronous Activity Processing Time.
Execution Time shows the elapsed processing time for the transaction segment and helps determine whether the request exceeded slow or very slow transaction thresholds. Thread Blocking Time identifies time during which the executing thread was blocked or waiting, potentially because of lock contention, synchronization, resource availability, or another thread-related delay. A substantial blocking value can explain why an otherwise ordinary code path produced a slow snapshot.
Asynchronous Activity Processing Time represents time consumed by asynchronous work associated with the transaction, such as executor tasks, callbacks, or background processing correlated with the originating request. Excessive asynchronous processing can materially increase end-to-end completion time and trigger snapshot collection.
Tier Response Time and Node Response Time are aggregated performance metrics across multiple transactions. They provide useful operational context but do not directly describe the timing characteristics of one captured transaction execution.
Relevant CAAPA Study Guide topics include Transaction Snapshots, Snapshot Flow Maps, Execution Time, Thread Blocking, Asynchronous Transaction Tracking, and Slow Transaction Diagnostics.
NEW QUESTION # 116
Which two health rules are provided out-of-the-box for proactive monitoring? (Choose two.)
Answer: C,E
Explanation:
AppDynamics provides out-of-the-box health rules that proactively identify abnormal Business Transaction response time and Business Transaction error rate.
The response-time health rule evaluates whether a Business Transaction's current average response time has risen significantly above its established baseline. This enables AppDynamics to detect performance degradation relative to normal behavior rather than relying exclusively on a fixed threshold that may not suit every transaction.
The error-rate health rule similarly identifies when the number or percentage of transaction errors is substantially higher than expected. This provides early warning of application failures, exceptions, unsuccessful requests, or downstream dependency problems before they affect a larger portion of users.
Web-container thread utilization, thread stalls, and transaction-rate changes can also be monitored by creating or configuring health rules, but the listed formulations are not the two standard proactive Business Transaction health rules represented here. AppDynamics health rules can generate warning or critical violations and then invoke policies for notifications, diagnostics, remediation, or external-system integration.
Relevant CAAPA Study Guide topics include Default Health Rules, Business Transaction Performance, Dynamic Baselines, Response-Time Monitoring, Error-Rate Monitoring, Health Rule Violations, and Policy Actions.
NEW QUESTION # 117
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